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A way to identify patients at risk for ER visits and observation stays, surface modifiable risk factors, and streamline patient outreach.
More than 144 million ER visits and observation stays occur in the U.S. annually, and for older patients, emergent visits often signal critical health challenges. Roughly two-thirds of older adults return to their homes after a visit, but during this period they are 20–25% more likely to experience functional disability and may experience a persistent decline in their community mobility.
Patients in the U.S. have more than 144 million ER visits and observation stays each year (1). Experts have concluded that some ER visits are avoidable (i.e. that they don’t require the intense resources of the ER or could have been avoided with better primary care). But other ER visits are clinically emergent and cannot be avoided. Even when a patient is not admitted to the hospital, emergent visits can be signals of critical health challenges—particularly for older adults.
Older adults often experience a period of heightened vulnerability to adverse outcomes following an ER visit or observation stay, and an initial ER visit can lead to repeat visits and increased risk of morbidity and mortality (2). Roughly two-thirds of older adults return home after an ER visit, but in the six months following, they are 20–25% more likely to experience functional disabilities and a persistent decline in their community mobility (3,4).
Older patients that required minimal assistance prior to a visit may enter a downward spiral, either from an acute injury or the exacerbation of a chronic condition. For example, patients who sustain a serious fall-related injury (a leading cause of ER visits for older adults) often begin to limit their daily activities, which can lead to a decline in their health. Alternatively, underlying risk factors and complications, such as depression or delirium, can intensify following an ER visit and result in adverse health outcomes.
ER visits and observation stays are becoming increasingly common, and as the number of elderly Americans grows, addressing the needs of patients at the greatest risk for visits is imperative (5,6). AI-based models can help healthcare organizations (HCOs) identify patients at risk for ER visits and observation stays, surface modifiable risk factors, and streamline patient outreach. Care teams can leverage AI-enhanced insights to promote continuity of care, proactively assess patients and screen for functional decline, reduce potentially avoidable adverse events, and improve health outcomes (7).
